Changeset d8dbe0f in tol

Timestamp:

Dec 22, 2009, 9:52:25 AM (17 years ago)

Author:

Jorge Pérez <josp.jorge@…>

Branches:

1941-docker-image-to-test, devel, master

Children:

0bd9e15

Parents:

7827bac

Message:

refs #823 : changing name to ANN.KDTree.xxx, updating sample.tol

git-svn-id: ​https://www.tol-project.org/svn/tolp/trunk@1866 be4846ae-f051-483a-831f-b64e7d08527f

Location:

tol/contrib/ANN

Files:

• sample.tol (modified) (1 diff)
• tolANN.cpp (modified) (5 diffs)

tol/contrib/ANN/sample.tol

@@ -1 +1 @@
 Real dim = 2;
-Matrix XY = Rand( 100000, dim, 0, 1 );
-Real id = KDTree.New( XY );
+Matrix XY = Rand( 20000, dim, 0, 1 );
+Real id = ANN.KDTree.New( XY );
 Real k = 10;
-Set KDTree.KSearch( id, Rand( 10000, dim, 0, 1 ), k );
-Real KDTree.Delete( id );
+Set ANN.KDTree.KSearch( id, Rand( 100000, dim, 0, 1 ), k );
+Real ANN.KDTree.Delete( id );

tol/contrib/ANN/tolANN.cpp

@@ -88 +88 @@
 
 //--------------------------------------------------
-DeclareContensClass(BDat, BDatTemporary, BDatKDTreeNew);
-DefExtOpr(1, BDatKDTreeNew, "KDTree.New", 1, 1, "Matrix",
+DeclareContensClass(BDat, BDatTemporary, BDatANNKDTreeNew);
+DefExtOpr(1, BDatANNKDTreeNew, "ANN.KDTree.New", 1, 1, "Matrix",
           "(Matrix points)",
           I2("Build a kd-tree and return its identifier. A kd-tree is a "
              "complex data structure useful to perform nearest neighbourhood "
              "searches. When the kd-tree is not needed any more it should be "
-             "relased with KDTree.Delete\n"
-             "See also KDTree.Delete, KDTree.RSearch, KDTree.KSearch",
+             "relased with ANN.KDTree.Delete\n"
+             "See also ANN.KDTree.Delete, ANN.KDTree.RSearch and "
+             "ANN.KDTree.KSearch",
              "Construye un kd-tree y retorna su identificador. Un kd-tree es "
              "una estructura de datos compleja util en la busqueda de "
              "vecinos cercanos. Cuando un kd-tree ya no se necesite mas debe "
-             "liberarse con KDTree.Delete\n"
-             "Vease tambien KDTree.Delete, KDTree.RSearch, KDTree.KSearch"),
+             "liberarse con ANN.KDTree.Delete\n"
+             "Vease tambien ANN.KDTree.Delete, ANN.KDTree.RSearch y "
+             "ANN.KDTree.KSearch"),
           BOperClassify::MatrixAlgebra_);
 //--------------------------------------------------
-void BDatKDTreeNew::CalcContens()
+void BDatANNKDTreeNew::CalcContens()
 {
   tol_kdtree *aux = NULL;
@@ -121 +123 @@
 
 //--------------------------------------------------
-DeclareContensClass(BDat, BDatTemporary, BDatKDTreeDelete);
-DefIntOpr(1, BDatKDTreeDelete, "KDTree.Delete", 1, 1,
+DeclareContensClass(BDat, BDatTemporary, BDatANNKDTreeDelete);
+DefIntOpr(1, BDatANNKDTreeDelete, "ANN.KDTree.Delete", 1, 1,
           "(Real kdtree)",
-          I2("Release a kd-tree previously created with KDTree.New. "
+          I2("Release a kd-tree previously created with ANN.KDTree.New. "
              "Returns 1 if success or 0 in case of fail.\n"
-             "See also KDTree.New, KDTree.RSearch, KDTree.KSearch",
-             "Libera un kd-tree previamente creado con KDTree.New. "
+             "See also ANN.KDTree.New, ANN.KDTree.RSearch and "
+             "ANN.KDTree.KSearch",
+             "Libera un kd-tree previamente creado con ANN.KDTree.New. "
              "Retorna 1 se libero exitosamente o 0 en caso de fallo.\n"
-             "Vease tambien KDTree.New, KDTree.RSearch, KDTree.KSearch"),
+             "Vease tambien ANN.KDTree.New, ANN.KDTree.RSearch y "
+             "ANN.KDTree.KSearch"),
           BOperClassify::MatrixAlgebra_);
 //--------------------------------------------------
-void BDatKDTreeDelete::CalcContens()
+void BDatANNKDTreeDelete::CalcContens()
 {
   double addr = Dat( Arg( 1 ) ).Value();
@@ -144 +148 @@
 
 //--------------------------------------------------
-DeclareContensClass(BSet, BSetTemporary, BSetKDTreeKSearch);
-DefExtOpr(1, BSetKDTreeKSearch, "KDTree.KSearch", 3, 3, "Real Matrix Real",
+DeclareContensClass(BSet, BSetTemporary, BSetANNKDTreeKSearch);
+DefExtOpr(1, BSetANNKDTreeKSearch, "ANN.KDTree.KSearch", 3, 3,
+          "Real Matrix Real",
           "(Real kdtree, Matrix qpoints, Real k)",
           I2("Computes for every point in points the k nearest neighbors. "
@@ -152 +157 @@
              "the neighbors and in the column 2 the squared distance to the "
              "query point. The index is referred to the ordering of the "
-             "points given in KDTree.New. The argument kdtree must be a "
-             "valid kdtree as returned from KDTree.New\n"
-             "See also KDTree.New, KDTree.Delete and KDTree.RSearch",
+             "points given in ANN.KDTree.New. The argument kdtree must be a "
+             "valid kdtree as returned from ANN.KDTree.New\n"
+             "See also ANN.KDTree.New, ANN.KDTree.Delete and "
+             "ANN.KDTree.RSearch",
              ""),
           BOperClassify::MatrixAlgebra_);
 //--------------------------------------------------
-void BSetKDTreeKSearch::CalcContens()
+void BSetANNKDTreeKSearch::CalcContens()
 {
   double addr = Dat( Arg( 1 ) ).Value();
@@ -199 +205 @@
   }
   assert( (buffer - ((DMat&)qpoints).GetData().GetBuffer()) ==
-          qpoints.Rows()*qpoints.columns() );
+          qpoints.Rows()*qpoints.Columns() );
   annDeallocPt( pt );
   delete [] nn_idx;